This invention relates in general to wireless telecommunications networks and applications and, in particular, to a method and system of performing interference analysis among cells in a telecommunications network. More particularly, the invention relates to a method and system of estimating the accuracy of interference analysis based on traffic/disturbance event correlations.
Without limiting the scope of the invention, its background is described in connection with identifying, analyzing and quantifying uplink/downlink interference in a wireless telecommunications network, as an example.
Present-day mobile telephony has spurred rapid technological advances in both wireless and wireline communications. The wireless industry, in particular, is a rapidly growing industry, with advances, improvements, and technological breakthroughs occurring on an almost daily basis. Many mobile or wireless telecommunications systems, among them the European GSM-system, have passed through several generations of advancements and development phases, and system designers are now concentrating on further improvements to such systems, including system refinements and the introduction of optional subscriber services.
Most wireless telecommunication systems are implemented as cellular telephone networks wherein a group of Base Transceiver Stations (BTS), or base stations are served by a centrally located switch. The switch is commonly referred to as a Mobile Switching Center (MSC). The base stations are spaced apart from each other by distances of between one-half and twenty kilometers. Each base station is assigned a number of two-way voice and control channels. The voice channels transmit voice signals to and from proximately located mobile stations, and transmit control information to and from these mobile stations, usually for the purpose of establishing a voice communications link.
A typical cellular telephone network also includes a group of interconnected MSCs, which operate in association with a Gateway Mobile Switching Center (GMSC) through which the cellular telephone network interconnects with a conventional Public Switched Telephone Network (PSTN). In addition, at least one Home Location Register (HLR) operates within the cellular telephone network. The HLR stores network subscriber information, including the identified location of current mobile stations within the network.
In response to an incoming call placed to a mobile station, the MSC queries the HLR to determine the current location of the mobile station. The HLR xe2x80x9clooks upxe2x80x9d the current location of the mobile station and contacts the currently serving MSC to pre-route the call and retrieve a temporary location directory number, which is utilized to route the call through the telecommunications network for termination of the call to the mobile station. The MSC instructs the base station serving the cell in which the mobile station is located to page the mobile station. Responding to the page, the mobile station requests assignment of a channel, and the network terminates the call through the serving MSC and over the assigned channel.
Calls by mobile subscribers can be affected by interference which can cause radio disturbance events which, in turn, limit the efficiency of the network. As such, it is important to identify those cells within the network, which are sources of and subject to radio disturbance events. Interference internal to the network often results from call activity within a specific network cell site. Cells that are sources of to disturbances are described as xe2x80x9coffenders.xe2x80x9d A radio disturbance event typically occurs during a cellular call, either on the downlink (from a base station to a mobile station), or on the uplink (from a mobile station to a base station). The disturbance event can be limited to several types of interference, including co-channel interference, adjacent channel interference or external interference.
Various methods exist for determining when a cell has been disturbed. Typically, a comparison of signal strength versus a measurement of speech quality can be employed to determine the Bit Error Rate (BER) of the transmission channel. When sufficient signal strength is correlated with degraded speech quality for an extended period of time (usually measured in seconds), that cell can be considered xe2x80x9cdisturbed.xe2x80x9d Failure to identify and analyze sources of such disturbances could result in poor channel quality and the sealing of devices, which means they are unavailable for use in handling calls.
Additionally, several methods and systems currently exist for identifying disturbed cells within the wireless telecommunications networks. One of the most widely utilized methods involves downlink interference prediction tools, or prediction methods, which use model-based prediction algorithms. Such tools predict where interference may exist within a given network coverage area. The predictions are then utilized for frequency and cell planning, particularly in initial network designs. The validity of such predictions is dependent on a number of factors, including the accuracy of the propagation model utilized and the resolution of the terrain data. Such tools are helpful in identifying the cells that are causing downlink interference, but taken together are often inaccurate because of the dependence on predictions. That is, such prediction tools do not always account for xe2x80x9creal-lifexe2x80x9d sources of interferences in the coverage area as determined through more empirical measurement methods.
Another method utilized to identify disturbed and offending cells involves drive testing by field personnel. The drive test can be performed by turning off all adjacent/co-channel transmitters for a particular disturbed cell and then keying up each transmitter individually. A drive test team, in the meantime, drives the area in a motorized vehicle to observe and measure interference within the drive area. This method is inherently labor intensive and costly since it requires continuous measurement by field personnel. In addition, the drive-test approach, while sometimes useful, does not take into account variations in mobile station types and is limited to the extent that only several possible offenders can be investigated.
The Related Application t (U.S. patent application Ser. No. 09/ 426,139) provides a cost effective method of identifying and analyzing sources of interference in the network that utilizes available qualitative data about the network. Essentially, the Related Application discloses a technique where traffic/disturbance event correlations are assembled and analyzed in order to narrow the field of possible offender cells for a specific disturbed cell. By relating disturbance events in one cell to traffic events (or call activity) in surrounding cells, a way of analyzing interference within the network is provided.
While the correlation technique of the Related Application is useful, there is no known way to quantify the accuracy of such traffic/disturbance xe2x80x9ccorrelationxe2x80x9d techniques. It is known that certain correlations are naturally occurring within the network without consideration of the interference factor. Such naturally occurring correlations can give a false sense of confidence in terms of positively being able to identify a disturbance source in the network. A way of taking into consideration the effect of false matches would therefore be advantageous. What is needed is a way of estimating the probability of false event correlations to confirm that call activity in one or more of the offending cells is the likely cause of interference in a given cell.
The present invention provides a method and system for quantifying the probability of false event correlations occurring from random matches in a telecommunications network. With the present invention, the network operator can use the probability of false event correlations to confirm that call activity in one or more of the offending cells is likely to be the cause of the interference in the given cell in designing the network, or improving performance.
Disclosed in one embodiment is a method of performing interference analysis among cells in a telecommunications network. For any given cell and a plurality of neighboring cells, the method comprises the step of computing a plurality of traffic/disturbance event correlations as a function of call activity in the neighboring cells and disturbance activity in the given cell.
The method further comprises the step of quantifying the probability of false event correlations occurring from random matches. In one embodiment, an estimation algorithm or xe2x80x9cdetectorxe2x80x9d is defined. Initially, the utilization of each offending cell""s channel is multiplied by the number of disturbance events on each disturbed cell""s channel as a function of time. The product of the utilization of each offending cell""s channel as a function of time and the number of disturbance events on each disturbed cell""s channel is then summed over all hours for all offending-disturbed channel pairs and for the offending-disturbed cell combination.
The method also comprises the step of defining the average ratio of the occurrence of random matches, which is proportional to the sum over all hours of the product of the utilization of the offender and the number of disturbances on the disturbed cell""s channel. The ratio of the two quantities when summed over a large amount of data yields a constant for the values associated with the occurrence of random matches greater than 20. That is, if the number of random matches is greater than 20, the number of matches is approximately equal to the quantity equal to the sum over all hours of the product of the utilization of the offender and the number of disturbances on the disturbed cell""s channel.
Based on the discovery of a system constant, it can be argued that for any offender-disturbed cell relationship, the average number of random matches is computed by multiplying the average ratio of the occurrence of random matches, which is proportional to the sum over all hours of the product of the utilization of the offender and the number of disturbances on the disturbed cell""s channel by the sum of the product of the utilization of each offending cell""s channel as a function of time and the number of disturbance events on each disturbed cell""s channel as a function of time over all hours for all offending-disturbed channel pairs and for the offending-disturbed cell combination. The probability of the difference between the average number of random matches and the number of random matches is then calculated in order to plot the percentage of difference from average values along the x-axis and the cumulative distribution function percentage values along the y-axis, which yields the cumulative distribution function of the percentage difference from the average value. As such, when the difference from average exceeds a certain threshold, the probability of a confirmed offender increases. That is, if the Cumulative Distribution Function (CDF) gives the probability that the Call Event Recording (CER) and Radio Disturbance Recording (RDR) correlations are not due to a random phenomenon, they result from an actual cause-effect relationship between the cells. In doing so, the method also comprises the step of identifying the value of the CDF of the percentage difference from the average in order to affirm the offender as a true interfering cell utilizing a percentage confidence level. That is, the percentage confidence level to affirm the offender as a true interfering cell probability utilizing the cumulative distribution function of the percentage difference from the average is computed.
The method further comprises the step of using the probability of false event correlations to confirm that call activity in one or more of the offending cells is likely to be the cause of the interference in the given cell. That is, in estimating the accuracy of interference analysis based on traffic/disturbance event correlations, the percentage confidence level to affirm the offender as a true interfering cell is compared with a decision threshold to decide if the interference relationship is true.
Technical advantages of the present invention include a less labor intensive method of identifying disturbed cells in the network compared to the drive testing approach. Sources of interference are identified in the shortest amount of time and by use of disturbance data already contained in the network. In addition, noise factors are considered in determining sources of interference.
Other technical advantages include more accurate identification and analysis of interference sources. The method and system of the present invention utilizes empirical measurements based on recorded disturbance events, and not predictions, and quantifies the probability of false event correlations occurring from random matches.